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## ----include = FALSE----------------------------------------------------------
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
warning = FALSE,
message = FALSE,
fig.width = 6,
fig.height = 4
)
## ----setup--------------------------------------------------------------------
library(glmbayes)
## ----menarche-fit-------------------------------------------------------------
data(menarche, package = "MASS")
Age2 <- menarche$Age - 13
Menarche_Model_Data <- data.frame(
Menarche = menarche$Menarche,
Total = menarche$Total,
Age2 = Age2
)
ps <- Prior_Setup(
cbind(Menarche, Total - Menarche) ~ Age2,
family = binomial(link = "logit"),
data = Menarche_Model_Data
)
fit_logit <- glmb(
cbind(Menarche, Total - Menarche) ~ Age2,
family = binomial(link = "logit"),
pfamily = dNormal(mu = ps$mu, Sigma = ps$Sigma),
data = Menarche_Model_Data,
n = 800,
use_parallel = FALSE
)
coef_draws <- as.matrix(fit_logit$coefficients)
## ----ppc-setup----------------------------------------------------------------
## Observed success proportions (aligned with simulate.glmb for binomial)
y_obs <- Menarche_Model_Data$Menarche / Menarche_Model_Data$Total
pred_resp <- predict(fit_logit, type = "response")
nd <- max(1L, min(50L, nrow(pred_resp)))
pred_sub <- pred_resp[seq_len(nd), , drop = FALSE]
y_rep <- stats::simulate(
fit_logit,
pred = pred_sub,
prior.weights = fit_logit$prior.weights
)
stopifnot(nrow(y_rep) == nd, ncol(y_rep) == length(y_obs))
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